id: 02220170
dt: j
an: 02220170
au: Hassanpour, Hamid; Mesbah, Mostefa; Boashash, Boualem
ti: Time-frequency feature extraction of newborn EEG seizure using SVD-based
    techniques.
so: EURASIP J. Appl. Signal Process. 2004, No. 16, 2544-2554 (2004).
py: 2004
pu: Hindawi Publishing Corporation, New York, NY
la: EN
cc: 
ut: detection; time-frequency distribution; singular value decomposition;
    probability distribution function
ci: 
li: doi:10.1155/S1110865704406167
ab: Summary: The nonstationary and multicomponent nature of newborn EEG
    seizures tends to increase the complexity of the seizure detection
    problem. In dealing with this type of problems, time-frequency-based
    techniques were shown to outperform classical techniques. This paper
    presents a new time-frequency-based EEG seizure detection technique.
    The technique uses an estimate of the distribution function of the
    singular vectors associated with the time-frequency distribution of an
    EEG epoch to characterise the patterns embedded in the signal. The
    estimated distribution functions related to seizure and nonseizure
    epochs were used to train a neural network to discriminate between
    seizure and nonseizure patterns.
rv: